December/January:

About This Technology

April 2001

High-performance computing is now in the mainstream of computing, thanks to a combination of higher-speed components and various approaches to parallel computing: within individual chips, among chips within individual computers, and among computer systems. Although trade-offs are necessary in the pursuit of speed and parallelism, designers, vendors, and sophisticated users try to extend both features simultaneously, while balancing the need for cost-effectiveness. The availability of various levels of computer power, in modular fashion, will enable many improvements in diverse areas ranging from genomic research to weather prediction and more mundane applications such as logistics-reconfiguring and e-commerce applications in real time. Moreover, the technology will be transparent to the recipients of the information.

The computer industry's search for higher-speed computing relies primarily on quick improvements in the design, development, and fabrication of microprocessors and memory, and their integration with other computer components. The general path to improving of individual chips remains true to the prediction of Gordon Moore, cofounder of Intel Corporation, some 30 years ago: By reducing the size of transistors in integrated circuits, manufacturers can increase computing power some 40% per year, while maintaining essentially the same costs. Capabilities that originally required specialized materials and designs are now available in computers for mainstream applications. To obtain even more computing power, designers link ever-faster components into ever-larger systems, using multiple microprocessors, large amounts of memory, and faster input and output devices. Parallelism, once available only in the highest-level computer systems—very expensive supercomputers—has moved into mainstream use within microprocessors, desktop computers and workstations, servers, and multiple computer systems,which can now operate as a unit.

Users will be the main beneficiaries of the technology, which will continue to broaden the range of computing power as necessary—incrementally and cost-effectively. Although the most publicized examples of high-performance computing are in the domains of esoteric science and technology—for example, the design and simulation of nuclear-power devices and reactions—the most common applications are commercial. Typical uses include data mining in large-scale databases for electronic commerce, animation of feature-length movies (such as Toy Story I and II, or enhancement of films with animations, simulations, and special effects (such as Titanic). Other applications, such as weather prediction and artificial intelligence, which have existed since the early days of computing, will continue to improve with additional computing power. Weather prediction will increase in accuracy and detail, whereas scientists will develop smarter programs that replicate human intelligence with greater fidelity than has been possible before now.